This Career Development proposal will support the training of Dr. David McFadden in mouse cancer models and genomics under the mentorship of Dr. Tyler Jacks with support from collaborators Drs. Meyerson, Hannon, Lander, and Getz. The candidate, Dr. McFadden, is trained in mouse genetics, internal medicine and endocrinology with a clinical practice devoted to the care of thyroid cancer patients. The mentor, Dr. Jacks, is an international leader in cancer research with a focus on the development and use of sophisticated mouse cancer models. Drs. Meyerson, Hannon, Lander, and Getz bring a wealth of expertise in human lung adenocarcinoma genetics, genomics, and bioinformatics. In this unique scientific environment, Dr. McFadden will have the opportunity to train in cancer biology and genomics in order to blend mouse cancer models with cutting edge genetic technology in order to identify novel targets for treatment in human cancer. The development of massively parallel DNA sequencing methodologies has fueled the detailed description of human cancer genomes. However, the functional relevance of specific mutations to the cancer phenotype has been more challenging to define. Carefully constructed mouse models of human cancer have been developed and utilized to carefully characterize all stages of tumorigenesis, including tumor initiation, progression, and metastasis. Although the genetically engineered mutations responsible for tumor induction in these models are known ab initio, the spectrum of mutations acquired during progression from hyperplasia to invasive neoplasm remains largely unknown. Studies have demonstrated that carefully constructed mouse models exhibit gene expression signatures and DNA copy number profiles that overlap with those detected in human cancers, suggesting that the selective pressures exerted on cancer cells are shared between mice and humans. These studies demonstrate the value of cross-species comparisons to identify functionally important driver genes that direct the diverse cellular processes that compose human cancer progression. Over this 5-year proposal, we will generate large-scale sequencing datasets from a mouse model of lung adenocarcinoma to identify the point mutations acquired during tumor evolution. We will perform cross- species comparative studies and pathway analyses to rank candidate genes and pathways of most interest, and precisely characterize the functional role of these alterations using genetically engineered mouse models and human cancer cells. Our preliminary data demonstrate that this approach is feasible. We have generated a murine lung adenocarcinoma tissue bank consisting of advanced, high-grade murine tumors, cell lines, and metastases and developed a hybridization-based enrichment platform for the capture and sequencing of cancer-relevant genes. Using this novel technology, we have sequenced murine lung adenocarcinoma cell lines and identified somatic mutations acquired during tumor progression.